Find exploitable AI weaknesses before they become incidents.
The Assessment Engine tests supported AI systems out-of-band using adaptive text and image attack surfaces, without sitting in the production traffic path.
Adaptive, not a fixed checklist.
The engine does not simply replay a static list of prompts. It learns from how the target responds, identifies which attack paths are landing, and develops the test further from there.
Generated attacks
Tests are built from the target’s role and responses, not only from a predefined prompt list.
Context-aware judging
The evaluator considers purpose, input, attack and output together to reduce meaningless findings.
Text and image pressure
Test text and image attack surfaces when the underlying model supports them.
What it tests
Risky interaction
A text or image prompt attempts to manipulate the system into exposing data or using an unauthorized tool.
Assessment
Adaptive red-teaming tests the attack path out-of-band and follows the system response.
Evidence
The finding records what was tested, what happened and the evidence behind the result; the test can be repeated after a change.
Agents
Prompt injection, exfiltration, permissions, tool misuse and supply-chain patterns.
Models and model APIs
Adversarial testing over common model and REST-style interfaces, including private inference.
MCP servers
Tool enumeration, permission analysis, input validation and MCP-specific attack patterns.
Skills and repositories
Inspect code and markdown artifacts and, where appropriate, probe behavior in an isolated environment.
A finding should tell you what to do next.
Each finding should answer four things: what attack worked, what the system did, what business impact it could create, and how to remediate it. Then the fix can be re-tested instead of assumed.
- What attack worked
- What the system did
- Business impact
- How to remediate
Continuous, not annual.
AI systems change constantly: prompts are tuned, tools are added and models are replaced. Assessment can be repeated around releases and changes so the security posture follows the system, not last quarter’s snapshot.
See how a supported assessment turns a risky interaction into an evidence-backed finding and a repeatable validation step.